J
Jane Scheetz
Researcher at University of Melbourne
Publications - 34
Citations - 666
Jane Scheetz is an academic researcher from University of Melbourne. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 8, co-authored 33 publications receiving 331 citations. Previous affiliations of Jane Scheetz include La Trobe University.
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Journal ArticleDOI
An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs
Zhixi Li,Stuart Keel,Chi Liu,Yifan He,Wei Meng,Jane Scheetz,Pei Ying Lee,Jonathan E. Shaw,Daniel S W Ting,Tien Yin Wong,Hugh R. Taylor,Robert T. Chang,Mingguang He +12 more
TL;DR: This artificial intelligence–based, deep learning algorithm can be used with high accuracy in the detection of vision-threatening referable DR in retinal images and offers potential to increase the efficiency and accessibility of DR screening programs.
Journal ArticleDOI
Feasibility and patient acceptability of a novel artificial intelligence-based screening model for diabetic retinopathy at endocrinology outpatient services: a pilot study.
Stuart Keel,Pei Ying Lee,Jane Scheetz,Zhixi Li,Mark A. Kotowicz,Mark A. Kotowicz,Mark A. Kotowicz,Richard J MacIsaac,Richard J MacIsaac,Mingguang He +9 more
TL;DR: AI-based DR screening in endocrinology outpatient settings appears to be feasible and well accepted by patients, and overall satisfaction and the preferred model of care are reported.
Journal ArticleDOI
Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma.
TL;DR: The findings suggest that this visualization method can highlight traditional regions in disease diagnosis, substantiating the validity of the deep learning models investigated and may promote the clinical adoption of these models.
Journal ArticleDOI
A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology
Jane Scheetz,Philip Rothschild,Myra B McGuinness,Xavier Hadoux,H. Peter Soyer,H. Peter Soyer,Monika Janda,James J.J. Condon,Luke Oakden-Rayner,Lyle J. Palmer,Stuart Keel,Peter van Wijngaarden +11 more
TL;DR: In this article, the authors conducted an online survey of fellows and trainees of three specialty colleges (ophthalmology, radiology/radiation oncology, dermatology) in Australia and New Zealand on artificial intelligence.
Journal ArticleDOI
Development and validation of a deep-learning algorithm for the detection of neovascular age-related macular degeneration from colour fundus photographs.
Stuart Keel,Zhixi Li,Jane Scheetz,Liubov Robman,Liubov Robman,James Phung,Galina Makeyeva,K. Z. Aung,Chi Liu,Xixi Yan,Wei Meng,Robyn H. Guymer,Robert T. Chang,Mingguang He,Mingguang He +14 more
TL;DR: This study highlights the importance of knowing the carrier and removal status of canine coronavirus, as a source of infection for macular degeneration, in patients withAMD.